A therapist's most profound responsibility is choosing the right treatment for his or her client. Yet despite extensive training, many mental health professionals have difficulty determining which interventions are best for a particular client at a particular time, and which ones are inert or might even be harmful. And even the most self-aware clinicians are susceptible to biases that can influence their decisions and can have a dramatic effect on treatment outcome.

In this book, the first of its kind, contributors apply the theory and research of decision analytics to mental health, with a focus on improving clinical decision making. Decision analytics is a rapidly expanding field that provides crucial insight into how we process information. In the mental health context, decision analytics considers psychotherapy theories as exercises in pattern recognition, and therapy itself as a unique combination of expertise and intuition on the part of the therapist, requiring snap judgments as well as long-term deliberation.

Contributors examine common decision-making biases, such as confirmation bias and the ""sunk-cost"" fallacy, which can lead to poor outcomes if ignored or left unchecked. Practical recommendations are provided for improving clinical decisions using evidence-based findings, client feedback, ethics, and more.